The Summer Institute for Training in Biostatistics II (SIBS II) will be offered by the Department o Biostatistics and Medical Informatics in collaboration with the Department of Statistics at the University of Wisconsin- Madison. The program will give approximately 20 undergraduate students majoring in the quantitative sciences the opportunity to explore a career in biostatistics and bioinformatics. It is recognized that the number of MS and PhD trained biostatisticians has not increased sufficiently to keep up with the dramatic increase in the number of available positions in academic, industry, and government medical research institutions. Our goal is to provide a summer program for undergraduate majors in mathematics, computer science, and other quantitative sciences to expose them to the field of biostatistics and its applications in basic and clinical research. We plan to show them the many career opportunities to apply mathematical science to develop new methods for design and analysis of resulting data. The ultimate goal is to stimulate their interest in this field such that they will apply to graduate scool in biostatistics, statistics or a related biomedical field. Over a six- week summer school session, participants will be engaged in two three-credit courses for a total of six credits that can transfr back to students' undergraduate institutions to complete part of their major or minor. The first course will be an Introduction to Biostatistics and will provide an overview of fundamental statistical concepts and a practical working knowledge of basic statistical techniques they are likely to encounter in applied research. A second course, Practicum in Basic Biostatistics, will give students exposure to analyzing data from basic science experiments, clinical trials, and observational studies. Data sets available in the department as well as those provided by the NHLBI and the UW Institute for Clinical and Translational Research (ICTR) will be assembled. After the students have been given sufficient training in the statistical language R, they will hav projects to discover the power of the statistical methods presented in the weekly lectures. Through this process, we believe that students will see the opportunities that biostatistics provides to contribute in a meaningful way to the progress of medical and population health research.